Papers44

#Reinforcement Learning

Language-based Trial and Error Falls Behind in the Era of Experience

Haoyu Wang, Guozheng Ma et al.Jan 29arXiv

Big language models are great at words but waste lots of time and energy when they try random actions in non-language games like Sudoku, Sokoban, 2048, FrozenLake, and Rubik’s Cube.

#SCOUT#Reinforcement Learning#Supervised Fine-Tuning

OCRVerse: Towards Holistic OCR in End-to-End Vision-Language Models

Intermediate

Yufeng Zhong, Lei Chen et al.Jan 29arXiv

OCRVerse is a new AI model that can read both plain text in documents and the visual structures in charts, webpages, and science plots, all in one system.

#Holistic OCR#Vision-Language Model#Supervised Fine-Tuning

LLM-in-Sandbox Elicits General Agentic Intelligence

Beginner

Daixuan Cheng, Shaohan Huang et al.Jan 22arXiv

This paper shows that giving an AI a safe, tiny virtual computer (a sandbox) lets it solve many kinds of problems better, not just coding ones.

#LLM-in-Sandbox#Agentic Intelligence#Reinforcement Learning

Agentic Reasoning for Large Language Models

Intermediate

Tianxin Wei, Ting-Wei Li et al.Jan 18arXiv

This paper explains how to turn large language models (LLMs) from quiet students that only answer questions into active agents that can plan, act, and learn over time.

#Agentic Reasoning#LLM Agents#In-Context Learning

Knowledge is Not Enough: Injecting RL Skills for Continual Adaptation

Intermediate

Pingzhi Tang, Yiding Wang et al.Jan 16arXiv

Big language models can learn new facts with simple tutoring (SFT), but that doesn’t automatically teach them how to use those facts well.

#Parametric Skill Transfer#Skill Vector#Task Arithmetic

MatchTIR: Fine-Grained Supervision for Tool-Integrated Reasoning via Bipartite Matching

Intermediate

Changle Qu, Sunhao Dai et al.Jan 15arXiv

MatchTIR teaches AI agents to judge each tool call step-by-step instead of giving the same reward to every step.

#Tool-Integrated Reasoning#Credit Assignment#Bipartite Matching

Re-Align: Structured Reasoning-guided Alignment for In-Context Image Generation and Editing

Beginner

Runze He, Yiji Cheng et al.Jan 8arXiv

Re-Align is a new way for AI to make and edit pictures by thinking in clear steps before drawing.

#In-Context Image Generation#Reference-based Image Editing#Structured Reasoning

SmartSearch: Process Reward-Guided Query Refinement for Search Agents

Intermediate

Tongyu Wen, Guanting Dong et al.Jan 8arXiv

SmartSearch teaches search agents to fix their own bad search queries while they are thinking, not just their final answers.

#Search agents#Process rewards#Query refinement

Aligning Text, Code, and Vision: A Multi-Objective Reinforcement Learning Framework for Text-to-Visualization

Intermediate

Mizanur Rahman, Mohammed Saidul Islam et al.Jan 8arXiv

This paper teaches a model to turn a question about a table into both a short answer and a clear, correct chart.

#Text-to-Visualization#Reinforcement Learning#GRPO

MiMo-V2-Flash Technical Report

Intermediate

Xiaomi LLM-Core Team, : et al.Jan 6arXiv

MiMo-V2-Flash is a giant but efficient language model that uses a team-of-experts design to think well while staying fast.

#Mixture-of-Experts#Sliding Window Attention#Global Attention

Falcon-H1R: Pushing the Reasoning Frontiers with a Hybrid Model for Efficient Test-Time Scaling

Beginner

Falcon LLM Team, Iheb Chaabane et al.Jan 5arXiv

Falcon-H1R is a small (7B) AI model that thinks really well without needing giant computers.

#Falcon-H1R#Hybrid Transformer-Mamba#Chain-of-Thought

VAR RL Done Right: Tackling Asynchronous Policy Conflicts in Visual Autoregressive Generation

Intermediate

Shikun Sun, Liao Qu et al.Jan 5arXiv

Visual Autoregressive (VAR) models draw whole grids of image tokens at once across multiple scales, which makes standard reinforcement learning (RL) unstable.

#Visual Autoregressive (VAR)#Reinforcement Learning#GRPO

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